A method for extracting stents in medical images is already known from the publication entitled “Deformable Boundary Detection of Stents in Angiographic Images”, by Ioannis Kompatsiaris et alii, in IEEE TRANSACTIONS ON MEDICAL IMAGING, VOL. 19, No. 6, JUNE 2000, pages 652-662. This document describes an image processing method for deformable boundary detection of medical tools, called stents, in angiographic images. A stent is a surgical stainless steel coil that is placed in a coronary in order to improve blood circulation in regions where a stenosis has appeared. A stenosis is a narrowing of the coronary. When a stenosis is identified in a coronary of a patient, a procedure Percutaneous Transluminal Coronary Angioplasty (PTCA) may be prescribed. A basic idea of PTCA is to position a monorail with a small inflatable balloon within the narrowed section of the coronary. The balloon is inflated in order to push outwards the wall of the narrowed coronary. This process reduces the narrowing until it no longer interferes with the blood flow. The balloon is then deflated and removed from the coronary. In order to avoid re-stenosis to occur in the previously stenosed region of the coronary, said process is often followed by a stent implantation performed in said region. The stent is introduced in the coronary using another balloon monorail. The stent is wrapped tightly around the second balloon attached to the monorail. Once this second balloon tipped monorail is positioned into said region of the coronary, the balloon is inflated. The deployment of the balloon causes the stent to expand, pressing it against the coronary wall. Then, the balloon and monorail are removed, while the stent, once expanded, can be considered as a permanent implant. This stent acts like a scaffold keeping the coronary lumen open and allowing normal blood flow to occur through the coronary. Stent placement helps many patients avoid emergency heart bypass interventions and/or heart attacks.
The method that is disclosed in the cited publication is focused on visibility of the stent after stent deployment in the angiographic images. It comprises the steps of forming 3D models of stents; deriving a set of 2D models using perspective rules; matching said 2D models with real angiographic images in a training phase; roughly detecting a stent in an angiographic image using the set of 2D models and maximum likelihood criteria; refining the borders of the roughly detected stent using an active contour model.
A drawback of said method is that the calculation load is too heavy for real time processing of a sequence of images in the intervention phase of stent implantation. Another drawback is that it does not provide the robustness and accuracy now required for stent implantation, as checked in a control step of stent positioning.